xiamuceer
66 lines
2.4 KiB
Python
66 lines
2.4 KiB
Python
"""章节重新生成相关的Schema定义"""
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from pydantic import BaseModel, Field
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from typing import Optional, List, Dict, Any
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from datetime import datetime
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class PreserveElementsConfig(BaseModel):
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"""保留元素配置"""
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preserve_structure: bool = Field(False, description="是否保留整体结构")
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preserve_dialogues: List[str] = Field(default_factory=list, description="需要保留的对话片段关键词")
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preserve_plot_points: List[str] = Field(default_factory=list, description="需要保留的情节点关键词")
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preserve_character_traits: bool = Field(True, description="保持角色性格一致")
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class ChapterRegenerateRequest(BaseModel):
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"""章节重新生成请求"""
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# 修改来源
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modification_source: str = Field("custom", description="修改来源: custom/analysis_suggestions/mixed")
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# 基于分析建议
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selected_suggestion_indices: Optional[List[int]] = Field(None, description="选中的建议索引列表")
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# 自定义修改指令
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custom_instructions: Optional[str] = Field(None, description="用户自定义的修改要求")
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# 保留配置
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preserve_elements: Optional[PreserveElementsConfig] = Field(None, description="保留元素配置")
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# 生成参数
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style_id: Optional[int] = Field(None, description="写作风格ID")
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target_word_count: int = Field(3000, description="目标字数", ge=500, le=10000)
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focus_areas: List[str] = Field(default_factory=list, description="重点优化方向")
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# 版本管理
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save_as_version: bool = Field(True, description="是否保存为新版本")
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version_note: Optional[str] = Field(None, description="版本说明", max_length=500)
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auto_apply: bool = Field(False, description="是否自动应用（替换当前内容）")
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class RegenerationTaskResponse(BaseModel):
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"""重新生成任务响应"""
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task_id: str
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chapter_id: str
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status: str
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message: str
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estimated_time_seconds: int = 120
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class RegenerationTaskStatus(BaseModel):
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"""重新生成任务状态"""
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task_id: str
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chapter_id: str
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status: str
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progress: int
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error_message: Optional[str] = None
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created_at: Optional[datetime] = None
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started_at: Optional[datetime] = None
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completed_at: Optional[datetime] = None
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# 结果信息
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original_word_count: Optional[int] = None
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regenerated_word_count: Optional[int] = None
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version_number: Optional[int] = None
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